A change-point model for identifying 3'UTR switching by next-generation RNA sequencing

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Next-generation RNA sequencing enables large-scale transcriptome investigation.
• Alternative polyadenylation (polyA) generates mRNA isoforms with varying 3' untranslated regions (3'UTRs), impacting mRNA stability, localization, and translation.
• Existing methods for analyzing 3'UTR switching often rely on incomplete polyA site annotations, posing a challenge for accurate detection.

Purpose of the Study:

• To develop a novel method for detecting 3'UTR switching directly from RNA sequencing data.
• To enable the analysis of 3'UTR variations without requiring prior knowledge of polyadenylation sites.
• To provide a tool for a deeper understanding of gene regulation mechanisms through alternative RNA processing.

Main Methods:

• A change-point model utilizing a likelihood ratio test is proposed for detecting 3'UTR switching.
• A directional testing procedure is developed to identify significant shortening or lengthening events in 3'UTRs.
• The method controls the mixed directional false discovery rate at a nominal level.

Main Results:

• The proposed method is the first to directly analyze 3'UTR switching without relying on polyA annotations.
• Simulation studies and real data applications demonstrate the method's power, accuracy, and feasibility.
• The approach effectively analyzes next-generation RNA sequencing data for 3'UTR variations.

Conclusions:

• The developed method addresses a critical gap in alternative RNA processing analysis tools.
• It offers valuable insights into gene regulation by analyzing 3'UTR switching from transcriptome data.
• The software is freely available for download, facilitating its adoption in research.